Roche Diabetes Care at the hybrid IDF 2022 meeting

Monday, December 5, 2022 - Thursday, December 8, 2022

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Exhibit info

Visit our Showroom, where you find more information on integrated Personalised Diabetes Management. Feel free to contact us for more information and visit our website.

Location

CCL and online

Exhibition

Roche Diabetes Care Showroom

Opening hours

Tuesday, December 6: 10:00 - 17:00

Wednesday, December 7: 10:00 - 17:00

Thursday, December 8: 10:00 - 17:00

The Global diabetes pandemic calls for new ways to drive access to innovation and personalised care

Wednesday, December 7, 2022
Time: 12:30 - 13:30

Auditorium II

Chairs: Viswanathan Mohan (India), Bruno Almeida (Portugal)

Agenda

Speaker

How data research, modeling, and digital innovation support improved care for people with diabetes in low and middle income countries

Abdul Basit
Baqai Institute of Diabetology & Endocrinology, Karachi, Pakistan

Full abstract

Self-monitoring of blood glucose is still a pivotal part in the management of type 2 diabetes

Viswanathan Mohan
Dr. Mohan's Diabetes Specialities Centre, Chennai, Tamil Nadu, India

Full abstract

integrated Personalised Diabetes Management helps to advance diabetes care in Thailand - a clinical example

Nitchakarn Laichuthai
King Chulalongkorn Memorial Hospital, Bangkok, Thailand

Full abstract

Abstracts & Posters

Peer Support for People with Diabetes By People with Diabetes: A Model of Emotional and Psychological Well-being

Oral Presentation
Thursday, Dec 8 2022, 12:40 - 12:45 hrs
E- Poster terminals in Pavilion 1, Poster Station 8
Presenting Author: Anum Anwar

Author: Anum Anwar, Mahpara Gul, Atif Munir, Sana Ajmal

Full abstract View poster

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Publications

Automated Bolus Advisor

Use of an Automated Bolus Calculator in MDI-Treated Type 1 Diabetes - The BolusCal Study, a randomized controlled pilot study

(Schmidt et al. Diabetes Care, 2012 May;35(5):984-90.)

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Use of an Insulin Bolus Advisor Improves Glycemic Control in Multiple Daily Insulin Injection (MDI) Therapy Patients With Suboptimal Glycemic Control: First results from the ABACUS trial

(Ziegler et al. Diabetes Care. 2013 Nov; 36(11):3613-9.)

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SMBG – System Performance

System Accuracy Evaluation of 43 Blood Glucose Monitoring Systems for Self-Monitoring of Blood Glucose According to DIN EN ISO 15197

(Freckmann et al. J Diabetes Sci Technol. 2012 Sep 1;6(5):1060-75.)

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System accuracy evaluation of 18 CE marked current generation blood glucose monitoring systems based on EN ISO 15197:2015

(Pleus et al. BMJ Open Diabetes Res Care. 2020, 8(1): e001067)

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Structured Testing and Pattern Analysis

Use of a Novel, Remotely Connected Diabetes Management System Is Associated with Increased Treatment Satisfaction, Reduced Diabetes Distress, and Improved Glycemic Control in Individuals with Insulin-Treated Diabetes: First Results from the Personal Diabetes Management Study

(Mora et al. Diabetes Technol Ther. 2017 Dec 1;19(12):715-22.)

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Evaluation of a new digital automated glycemic pattern detection tool

(Comellas et al. Diabetes Techno Ther. 2017 Nov 1;19(11):633-40)

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Use of Diabetes Data Management Software Reports by Health Care Providers, Patients With Diabetes, and Caregivers Improves Accuracy and Efficiency of Data Analysis and Interpretation Compared With Traditional Logbook Data: First Results of the Accu-Chek Connect Reports Utility and Efficiency Study (ACCRUES)

(Hinnen et al. J Diabetes Sci Technol. 2015 Mar:9(2):293-301.)

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What Do We Need beyond Hemoglobin A1c to Get the Complete Picture of glycemia in people with diabetes?

(Hinzmann et al. Int. J Med Sci. 2012;9(8):665-81.)

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CGM

A Prospective Multicenter Evaluation of the Accuracy of a Novel Implanted Continuous Glucose Sensor: PRECISE II

(Christiansen et al. Diabetes Technol. Ther. 2018 Jan 30 (Epub))

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Accuracy and Longevity of an Implantable Continuous Glucose Sensor in the PRECISE Study: A 180-Day, Prospective, Multicenter, Pivotal Trial

(Kropff et al. Diabetes Care 2017 Jan:40(1):63-68.)

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Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space

(Heinemann et al. J Diabetes Sci Technol. 2019 Jun (Epub))

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Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice

(Johnson et al. J Diabetes Sci Technol. 2019 Jun:21(S2):S217-5225.)

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Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space

(Heinemann et al. J Diabetes Sci Technol. 2020 Jan;14(1):135–150.)

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Intermittent Use of Continuous Glucose Monitoring: Expanding the Clinical Value of CGM

(Ziegler et al. J Diabetes Sci Technol. 2021 May;15(3):684-694.)

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Standardization process of continuous glucose monitoring: Traceability and performance

(Freckmann et al. Clin. Chim. Acta. 2021 Apr;515:5-12.)

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CSII

Boluses in insulin therapy: A Commentary

(Ziegler et al. J Diabetes Technol. 2017;11(1):165-71.)

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Insulin pump therapy, multiple daily injections, and cardiovascular mortality in 18 168 people with type 1 diabetes: observational study

(Steineck et al. BMJ 2015; 350: h3234.)

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Open Source Closed-Loop Insulin Delivery Systems: A Clash of Cultures or Merging of Diverse Approaches?

(Barnard et al. J Diabetes Sci Technol. 2018 Nov;12(6):1223-1226)

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Patch Pumps: Are They All the Same?

(Heinemann et al. J Diabetes Sci Technol. 2019 Jan:13(1):34-40.)

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Establishing Methods to Determine Clinically Relevant Bolus and Basal Rate Delivery Accuracy of Insulin Pumps

(Kamecke et al. J Diabetes Sci Technol. 2018; ePub)

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Occlusion Detection Time in Insulin Pumps at Two Different Basal Rates

(Freckmann et al. J Diabetes Sci Technol. 2018;12(3):608-613)

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Continuous subcutaneous insulin infusion: Special needs for children

(Adolfsson et al. Pediatr. Diabetes 2017 Jan;18(4):225-261.)

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Using insulin pump with a remote-control system in young patients with diabetes improves glycemic control and enhances patient satisfaction

(Deeb et al. Clin. Diabetes Endocrinol. 2019 Jun 6;5:7.)

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Accuracy of Bolus and Basal Rate Delivery of Different Insulin Pump Systems

(Freckmann et al. Diabetes Technol. Ther. 2019 Apr;21(4):201-208)

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Comparative Handling Analysis of Different Insulin Pump Systems

(Waldenmaier et al. J Diabetes Sci Technol. 2018 Mar;12(2):401-406)

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Concept and Implementation of a Novel Patch Pump for Insulin Delivery

(Ulbrich et al. J Diabetes Sci Technol. 2019 Aug (Epub))

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Concept and Implementation of a Novel Patch Pump for Insulin Delivery

(Ulbrich et al. J Diabetes Sci Technol. 2020 Mar;14(2):324-327.)

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Analysis of the Waste Volume and CO 2-Equivalent Caused by the Use of Selected Patch Pumps

(Winkelkötter et al. J Diabetes Sci Technol. 2021 (Epub))

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Insulin Pump Therapy for Patients With Type 2 Diabetes Mellitus: Evidence, Current Barriers, and New Technologies

(Freckmann et al. J Diabetes Sci Technol. 2020 (Epub))

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Accuracy assessment of bolus and basal rate delivery of different insulin pump systems used in insulin pump therapy of children and adolescents

(Ziegler et al. Pediatr. Diabetes. 2020 Jun;21(4):649-656.)

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Evaluation of the Accuracy of Current Tubeless Pumps for Continuous Subcutaneous Insulin Infusion

(Ziegler et al. Diabetes Technol. Ther. 2021 May;23(5):350-357.)

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Digital Solutions

Utilizing eHealth and Telemedicine Technologies to Enhance Access and Quality

(Barnard et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821.)

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A Digital-First Model of Diabetes Care

(Cafazzo et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821))

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Real-World Assessments of mySugr Mobile Health App

(Debong et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821)

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Use of Artificial Intelligence to Improve Diabetes Outcomes in Patients Using Multiple Daily Injections Therapy

(Forlenza et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821)

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The Emerging Role of Telemedicine and Mobile Health Technologies in Improving Diabetes Care

(Garg et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821)

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Current Status and Future Directions for Electronic Point-of-Care Clinical Decision Support to Improve Diabetes Management in Primary Care

(O'Connor et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821.)

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Use of Telemedicine Technologies in Diabetes Prevention and Control in Resource-Constrained Settings - Lessons Learned from Emerging Economies

(Pradeepa et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821)

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Virtual Coaching to Enhance Diabetes Care

(Ramchandani et al. J Diabetes Sci Technol. 2017 Jul;11(4):814-821.)

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Integrated Personalised Diabetes Management

Benefit of Digital Tools Used for Intergrated Personalized Diabetes Management: Results From the PDM-ProValue Study Program

(Heinemann et al. J Diabetes Sci Technol. 2019 Aug (Epub))

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Patient-centred care in type 2 diabetes mellitus - key aspects of PDM-ProValue are reflected in the 2018 ADA/EASD consensus report

(Fritzen et al. Diabetes Res. Clin. Pract. 2019 Dec (Epub))

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Intergrated personalized diabetes management improves glycemic control in patients with insulin-treated type 2 diabetes: Results of the PDM-ProValue study program

(Kulzer et al. Diab. Res. Clin. Pract. 2018 Oct;144:200-2012)

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Intergrated Personalized Diabetes Management (PDM): Design of the ProValues Studies: Prospective, Cluster-Randomized, Controlled, Intervention Trials for Evaluation of the Effectiveness and Benefit of PDM in Patients With Insulin-Treated Type 2 Diabetes.

(Kulzer et al. J Diabetes Sci Technol. 2016 May;10(3):722-781.)

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PDM-ProValue meets cardiovascular outcome trials in diabetes

(Fritzen et al. Cardiovasc. Diabetol. 2019 Jan 28;18(1):10)

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Chronic Kidney Disease

Predicting the early risk of chronic kidney disease in patients with diabetes using real-world data

(Ravizza et al. Nat Med. 2019 Jan:25(1):57-59.)

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Other

Modeling of Diabetes and Its Clinical Impact

(Fritzen et al. Diabetes Sci Technol. 2018 Sep;12(5):976-984.)

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Diabetes management intervention studies: lessons learned from two studies

(Petersen et al. Trials, 2021 Jan 18;22(1):61.)

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CIPII

Continuous intraperitoneal insulin infusion: an alternative route for insulin delivery in type 1 diabetes

(Pasquini et al. Acta Diabetol. 2019 Aug 9.)

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A New Optimized Percutaneous Access System for CIPII

(Garcia-Verdugo et al. J Diabetes Sci Technol. 2019 Jul;11(4):814-821)

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Intraperitoneal insulin delivery provides superior glycaemic regulation to subcutaneous insulin delivery in model predictive control-based fully-automated artificial pancreas in patients with type 1 diabetes: a pilot study

(Dassau et al. Diabetes Obs. Metab. 2017 Dec;19(12):1698-1705.)

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New Design of a Percutaneous Port System for Continuous Intraperitoneal Insulin Infusion

(Rieger et al. J Diabetes Sci Technol. 2019 Jun (Epub))

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Automated Insulin Delivery

Overnight closed-loop control improves glycemic control in a multicenter study of adults with type 1 diabetes

(Brown et al. Clin. Endocrinol. Metab. 2017 Oct 1;102(10):3674-3682.)

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Twelve-week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin a1c and Hypoglycemia

(Dassau et al. Diabetes Care 2018 Dec;40(12):1719-1726.)

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Closed-Loop Control During Intense Prolonged Outdoor Exercise in Adolescents With Type 1 Diabetes: The Artificial Pancreas Ski Study

(Breton et al. Diabetes Care 2017 Dec;40(12):1644-1650.)

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Closed-Loop Control Without Meal Announcement in Type 1 Diabetes

(Cameron et al. Diabetes Technol. Ther. 2017 Sep;19(9):527-532.)

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Artificial Pancreas: Clinical Study in Latin America Without Premeal Insulin Boluses

(Sanchez-Pena et al. J Diabetes Sci Technol. 2018 Sep;12(5):914-925.)

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Day-and-Night Closed-Loop Control Using the Unified Safety System in Adolescents With Type 1 Diabetes at Camp.

(Ly et al. Diabetes Care 2016 Aug;39(8):e 106-7.)

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Outpatient Closed-Loop Control With Unannounced Moderate Exercise in Adolescents Using Zone Model Predictive Control

(Huyett et al. Diabetes Technol. Ther. 2017 Jun;19(6):331-339.)

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Randomized Controlled Trial of Mobile Closed-Loop Control

(Kovatchev et al. Diabetes Care 2020 Mar;43(3):607-615.)

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Brochures - Our Solutions

Highlights

Accu-Chek Insight Loop Mode

Intelligent: DBLG1 algorithm analyses data in real time and is a self-learning algorithm, meaning it adapts to every individual.
Control everything with one device: Insulin and CGM values
Pre-filled NovoRapid insulin cartridge: No need to fill it by hand

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RocheDiabetes Care Platform

All-in-one platform which enables integrated Personalised Diabetes Management (iPDM)
Seamless connection with 150+ diabetes management devices and mySugr patient app, encouraging diabetes self-management
Actionable insights for more efficient consultations
Now with Customer Population Insights Dashboard, providing population analytics for HCPs, Admins, and Payers
Patient tracking and therapy adjustment for personalised care
Under constant evolution to support you now and in the future

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RocheDiabetes RemoteCare

Visualisation of all your patients at a glance to easily understand their status and prioritise them according to their needs
Quick and comprehensive picture of how patients are doing between visits, enabling remote interventions for continuous care
Two-way dialogue between HCPs and patients to enable proactive, flexible, and efficient care even at a distance
Recordings of observations and time spent providing remote care for potential reimbursement

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mySugr Pump Control

All data in one place: Patients can manage their CGM, BGM and pump data in just one app*.
Discretion: Send a bolus via the mySugr app discreetly anywhere, anytime.
Open bolus advisor: Directly accessible via the mySugr app
Freedom of choice: Choose from two pre-filled cartridges - Fiasp or NovoRapid.

*For all mySugr supported devices

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Accu-Chek Solo

First detachable and tube-free insulin pump
Unique quick bolus buttons on pump
Diabetes Manager with open bolus advice to combine therapy with continuous glucose monitoring solutions
Connected to the RocheDiabetes Care Platform, allowing the combined visualisation of insulin and blood glucose data to detect therapy patterns and improve outcomes

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Smart Pen Integration in mySugr Logbook

All-in-one: Manage glucose levels, insulin, and carb data in just one app.
Easy: Automated logging of insulin time and dose together with glucose values
Multiple pen pairing: Option to connect up to 8 pens
Intuitive visualisation: Valuable insights on patterns and therapy effectiveness

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Visit us

Visit our Roche Diabetes Care Showroom and find more information on integrated Personalised Diabetes Management. Feel free to contact us and visit our website.